Finished product rate management system and method for spunlace non-woven fabric production workshop

Abstract

The invention discloses a finished product rate management system and method for a spunlace non-woven fabric production workshop, and relates to the field of finished product rate management, and the system comprises a raw material management and source control module, an environment monitoring module, an equipment maintenance module, a production process monitoring module, and a quality inspection module. A multi-dimensional management system is formed through the measures of strictly screening raw material suppliers, casually inspecting raw materials, controlling the workshop environment, maintaining equipment, monitoring parameters, monitoring production indexes in real time, strictly inspecting finished products and the like, and the yield of spunlace non-woven fabric production workshops is increased. According to the method, full-process closed-loop management and control is formed through multi-dimensional monitoring and quick response, an innovative solution is provided for efficient operation of the spunlace non-woven fabric production workshop, and the yield management level of the spunlace non-woven fabric production workshop is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of yield rate management, and in particular to a yield rate management system and method for a spunlace nonwoven fabric production workshop. Background Art

[0002] In the field of spunlace non-woven fabric production, the improvement of finished product rate is constrained by the shortcomings of management in multiple links; on the raw material side, the screening and evaluation of suppliers of flame-retardant fibers, coatings, etc. lacks a standardized vertebral system, and the physical property sampling and quality traceability mechanism is imperfect; the execution of equipment maintenance plans is scattered and difficult to deal with in a timely manner; online detection of the production process is lagging, and the data of each link is scattered, and the support analysis is insufficient; the refinement of quality inspection standards and the closed-loop rectification are both missing, and problems are prone to recurrence; the existing model has significant defects in the systematicness of the entire process, parameter correlation, and closed-loop rectification. It is urgent to build an integrated management system covering "raw materials-environment-equipment-production-inspection" to break through the bottleneck of quality and efficiency.

[0003] The prior art includes a spunlace nonwoven fabric yield management system disclosed in the invention application patent with announcement number CN117152545A. The present invention discloses a spunlace nonwoven fabric yield management system, which includes six modules: an image acquisition module, which collects the surface image of the nonwoven fabric to be inspected and a defect-free reference image; an image feature extraction module, which inputs the two into a twin detection model to generate a surface detection and reference feature matrix; an image difference capture module, which calculates the transfer matrix between the two; a spatial feature enhancement module, which processes the transfer matrix through a spatial attention module to obtain a classification feature matrix; a feature optimization module, which optimizes its feature distribution; and a defect detection module, which determines whether a surface defect exists through a classifier.

[0004] Combining the above solutions, it can be found that the current spunlace non-woven fabric production workshop yield management system has limitations. The existing technology has extensive raw material management and lack of quality traceability, lack of production workshop environmental control, lagging equipment maintenance, untimely detection of production process indicators, no complete production workshop monitoring mechanism, and data dispersion and difficulty in analysis, lack of quality inspection closed loop, etc., which makes it difficult to control the non-woven fabric yield in time and difficult to meet the yield management needs of spunlace non-woven fabric production workshops. Summary of the Invention

[0005] The purpose of the present invention is to provide a spunlace nonwoven fabric production workshop yield management system and method, which solves the problems existing in the background technology.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions: A first spunlace nonwoven fabric production workshop yield management system of the present invention comprises: a spunlace nonwoven fabric related data collection module, for collecting relevant data of a batch of spunlace nonwoven fabrics, the relevant data including raw material data, production workshop data and finished product data;

[0007] The raw material qualification performance evaluation module is used to evaluate the raw material qualification index of this batch of spunlace nonwoven fabrics based on the raw material data of the spunlace nonwoven fabrics;

[0008] The production workshop performance evaluation module is used to evaluate the production performance qualification index of this batch of spunlace nonwovens based on the raw material data of spunlace nonwovens, including the workshop environment compliance index, equipment operation performance index and production process product qualification index, and evaluate the impact of various aspects of the production workshop on the finished spunlace nonwovens;

[0009] Finished product performance evaluation module, used to evaluate the finished product qualification index of spunlace nonwovens based on the finished product data of spunlace nonwovens;

[0010] The finished product qualification index abnormal traceability module is used to trace the raw materials and production link data based on the finished product qualification index of this batch of spunlace non-woven fabrics. When the finished product rate is abnormal, it can locate the cause and propose improvement measures.

[0011] A second aspect of the present invention provides a method for implementing a yield management system for a spunlace nonwoven fabric production workshop, comprising: S1. collecting data related to the spunlace nonwoven fabric, for collecting data related to a batch of spunlace nonwoven fabrics, the data including raw material data, production workshop data, and finished product data;

[0012] S2. Raw material qualification performance evaluation, used to evaluate the raw material qualification index of this batch of spunlace nonwoven fabrics based on the raw material data of the spunlace nonwoven fabrics;

[0013] S3. Production workshop performance evaluation, based on the raw material data of spunlace nonwovens, is used to evaluate the production performance qualification index of this batch of spunlace nonwovens, including the workshop environment compliance index, equipment operation performance index, and production process product qualification index, and to assess the impact of various aspects of the production workshop on the finished spunlace nonwovens;

[0014] S4 finished product performance evaluation is used to evaluate the finished product qualification index of spunlace nonwovens based on the finished product data of spunlace nonwovens;

[0015] S5 finished product qualification index abnormal traceability is used based on the finished product qualification index of this batch of spunlace non-woven fabrics. When the finished product rate is abnormal, it can trace the raw materials and production link data, locate the cause and propose improvement measures.

[0016] The beneficial effects of the present invention are: 1. In the raw material management and source control module, the present invention evaluates the qualifications of each raw material supplier through standardized screening, batch sampling of fiber length, strength and other properties, establishes a quality traceability system, and realizes controllable and traceable raw materials.

[0017] 2. In the equipment maintenance module, the present invention formulates a regular maintenance plan, monitors equipment parameters in real time and issues early warnings for abnormalities, thereby reducing unplanned downtime.

[0018] 3. In the production process monitoring module, the present invention detects thickness / weight and other indicators online, marks defective products in real time and integrates data from all links to provide support for abnormal analysis.

[0019] 4. In the quality inspection module of the present invention, a full-time position is set up to conduct random inspections according to various performance standards, trace the source of unqualified batches and make rectifications, thus forming a closed loop of quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0022] Figure 2 This is a connection diagram for executing the method of the present invention. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0024] Reference Figure 1 As shown, the present invention provides a finished product rate management system for a spunlace non-woven fabric production workshop, including: a spunlace non-woven fabric related data collection module, used to collect relevant data of this batch of spunlace non-woven fabrics, and the relevant data includes raw material data, production workshop data and finished product data.

[0025] It should be noted that suppliers of raw materials required for production are strictly screened and evaluated. Specifically, supplier access standards are established, and qualifications including production licenses, quality certifications, recent supply qualification rates, and R&D capabilities are reviewed. Through on-site factory inspections, we understand the supplier's production equipment, quality inspection processes, and historical cooperation data including delivery cycles, customer complaint rates, etc., and conduct quantitative assessments and classify them into the "core / alternative" library. Raw materials are sampled and traced, and samples are randomly taken from batches to test physical properties. A unique QR code is assigned to each batch of raw materials, which is linked to supplier information, test reports, and production lines used to build a "raw materials-production line-finished product" full-chain traceability database.

[0026] In a specific embodiment of the present invention, the data related to the spunlace nonwoven fabric is collected, and the data related to the spunlace nonwoven fabric includes raw material data, production workshop data, and finished product data, which specifically include:

[0027] Raw material data includes the total number of samples inspected, the number of samples that meet all performance requirements in the inspection batch, the fiber length of each sample, the fiber strength of the sample, and the fiber fineness of the sample;

[0028] Production workshop data includes workshop environment data, workshop equipment data, and online production process data. The workshop environment data includes the temperature, humidity, and air particle concentration of each monitoring point in the spunlace nonwoven production workshop at each time point. The workshop equipment data includes the duration of machine failure downtime, the real-time pressure of the spunlace head at each time point, the current total slitting length, and the machine failure downtime. The online production process data includes the weight of the product, the real-time width, the defect area, and the number of defects.

[0029] Finished product data includes the appearance qualification value, temperature, absorbance at a specific wavelength, burning time, and damaged area of ​​each finished product sample; due to the different dimensions of the data in the calculation, the data needs to be normalized and the collected data needs to be quantified into values ​​between 0 and 1.

[0030] The raw material qualification performance evaluation module is used to evaluate the raw material qualification index of this batch of spunlace nonwoven fabrics based on the raw material data of the spunlace nonwoven fabrics.

[0031] In a specific embodiment of the present invention, the method for evaluating the raw material qualification index of the spunlace nonwoven fabric of this batch based on the raw material data of the spunlace nonwoven fabric specifically includes:

[0032] A1. Extract the raw material data of spunlace nonwoven fabrics from the relevant data of spunlace nonwoven fabrics and evaluate the qualified rate of the raw materials of this batch of spunlace nonwoven fabrics. i=1,2,...,e, i is any integer greater than 2, which is the sample number of the random inspection, where N i is the number of samples that meet all performance requirements in the random inspection batch; when R≥R′, the raw material quality is stable; when R<R′, R′ is the raw material qualification rate threshold of the spunlace nonwoven production workshop;

[0033] A2. Evaluate the qualified index of the physical properties of this batch of spunlace non-woven fabric raw materials i=1,2,...,e, i is any integer greater than 2, and is the sample number for random inspection, Q i Indicates whether the physical properties of the raw fiber of spunlace nonwoven fabric are qualified.

[0034] Q i =0 means the fiber physical properties are qualified, Q i=1 means the fiber physical properties are unqualified, is the fiber length deviation of the ith sample of spunlace nonwoven fabric, is the fiber fineness deviation of the i-th sample,

[0035] is the fiber strength deviation of the i-th sample.

[0036] The production workshop performance evaluation module is used to evaluate the production performance qualification index of this batch of spunlace non-woven fabrics based on the raw material data of spunlace non-woven fabrics, including the workshop environment compliance index, equipment operation performance index and production process product qualification index, and evaluate the impact of various aspects of the production workshop on the finished spunlace non-woven fabrics.

[0037] In a specific embodiment of the present invention, the evaluation of the workshop environment compliance index specifically includes: evaluating and obtaining the workshop environment compliance index of the current batch of spunlace nonwoven fabrics based on the workshop environment data of the spunlace nonwoven fabrics,

[0038] B1. Record the temperature of each monitoring point at each time point. The difference between the highest and lowest temperatures at the same monitoring point within a fixed period is the temperature fluctuation value of the monitoring point, and the temperature stability index is obtained. j=1,2,...,n, j is any integer greater than 2, which is the number of the monitoring point, where T j is the temperature fluctuation value of the jth monitoring point;

[0039] B2. Record the temperature difference of each monitoring point to obtain the humidity stability index m=1,2,...,q, m is any integer greater than 2, and temperature and humidity sensors are used to collect data, where H m is the humidity value at the mth moment, is the average humidity;

[0040] B3. Based on the workshop environment data of spunlace nonwoven fabrics, and after data processing, the cumulative time that the air particle concentration in the production workshop of this batch of spunlace nonwoven fabrics continuously meets the cleanliness standard is obtained, and the cleanliness compliance rate in the production workshop is obtained. where t d is the cumulative time during the production period when the air particle concentration continues to meet the cleanliness standard, and t′ is the actual operating time from the start to the shutdown of the production line.

[0041] It should be noted that spunlace non-woven fabric production workshops are usually equipped with environmental control systems. Through real-time monitoring and control of the temperature, humidity and cleanliness of the production workshop, the environmental parameters are ensured to be stable within the allowable range of the process, reducing problems such as fiber static electricity, uneven curing of flame retardants, and abnormal product moisture content caused by environmental fluctuations, thereby directly improving the yield and performance consistency of flame-retardant / fire-resistant non-woven fabric tapes.

[0042] In a specific embodiment of the present invention, the specific steps of evaluating the equipment operation performance index are: evaluating and obtaining the production process product qualification index of this batch of spunlace nonwoven fabrics based on the workshop equipment data of the spunlace nonwoven fabrics;

[0043] C1. Pressure management of water jet nozzles in workshop equipment, pressure deviation value P of water jet nozzles w =|P ws -P′|, where P ws is the real-time pressure of the water jet of the w-th device, and P′ is the set pressure of the water jet;

[0044] C2. Management of wear life of slitting knife in workshop equipment, wear index of slitting knife Where W wt is the current total cutting length of the w-th device, and W′ is the upper limit of the blade cutting life;

[0045] C3. Workshop equipment failure management, equipment failure downtime rate Among them B 停 is the machine downtime, and B′ is the planned production time.

[0046] In a specific embodiment of the present invention, the step of evaluating the qualified index of the products in the production process comprises: evaluating and obtaining the qualified index of the products in the production process of the current batch of spunlace nonwoven fabrics based on the online data of the production process of the spunlace nonwoven fabrics;

[0047] D1. Online qualified rate of weight Among them G f is the number of each area of ​​the product with a grammage within the standard range, and b is the total number of monitored areas of the product;

[0048] D2. Width deviation ΔE k =|E k -E′|, where E i is the real-time width of the product produced by the kth roll, and E′ is the standard width;

[0049] D3. Defect area where X k is the kth defect area of ​​the product, and h is the total number of defects detected on the product.

[0050] In a specific embodiment of the present invention, the specific steps of evaluating the impact of various aspects of the production workshop on the finished spunlace nonwoven fabric are as follows:

[0051] Workshop environment compliance index

[0052] When N=0, it means that the workshop environment conformity index meets the standard; when N=1, it means that the workshop environment conformity index does not meet the standard. is the maximum threshold of temperature fluctuation value, is the maximum threshold of humidity stability, D max is the maximum threshold value of cleanliness compliance rate;

[0053] Equipment operation performance index

[0054] When M=0, it means that the equipment operation performance index meets the standard; when M=1, it means that the equipment operation performance index does not meet the standard. max is the maximum threshold of the water jet head pressure deviation value, W max is the maximum threshold of the slitting knife wear index, B max The maximum threshold for the equipment failure downtime rate.

[0055] The finished product performance evaluation module is used to evaluate the finished product qualification index of the spunlace nonwoven fabric based on the finished product data of the spunlace nonwoven fabric.

[0056] In a specific embodiment of the present invention, the evaluation of the qualified index of the finished product of the spunlace nonwoven fabric is specifically to sample each batch of products, take 1 meter samples at the beginning, middle and end of each roll, avoid end face errors, and conduct inspection and determine whether it is qualified, which specifically includes:

[0057] Finished product appearance qualified value a=1,2,...,r, where r is any integer greater than 2 and is the number of the sample taken, X is the qualified value of the finished product appearance, and M′ is the standard area of ​​a single roll;

[0058] Vertical burning test value Where T 自熄 T is the time it takes for the sample to extinguish itself after burning. 标 is the standard time for self-extinguishing, C 损毁 is the damaged length of the sample after combustion, C 标 It is the standard damaged length after burning. When Y=1, the finished non-woven fabric of this batch is qualified; when Y=0, the finished non-woven fabric of this batch is unqualified.

[0059] Moisture content of spunlace nonwoven finished products in T a The actual surface temperature of the cloth is the ath sample, which is T 标 is the standard calibration temperature, A a1450 is the absorbance of water molecules in the ath sample at a wavelength of 1450nm infrared light, A a1300 is the reference absorbance of water molecules in the ath sample at a wavelength of 1300nm infrared light, is the fiber background absorption, in order to eliminate the material difference, ε, β, γ are weight coefficients, when K a ≥K maxWhen K min <K a <K max When K a ≤K min When the moisture content of the finished product reaches the standard; (X max ,X min ) Specifically, the maximum and minimum values ​​of the qualified appearance of the finished product;

[0060] According to the finished product appearance qualified value, vertical burning test value and finished product moisture content of the spunlace non-woven fabric finished product samples, the finished product qualified index A=X×g1+Y×g2+K×g3 is obtained, where g1, g2, and g3 are the weight coefficients of the finished product appearance qualified value, vertical burning test value, and finished product moisture content, respectively, and g1+g2+g3=1.

[0061] It should be noted that the qualified value of the finished product appearance includes defects on the fabric, such as holes, stains, tears, and impurities attached; surface flatness, whether there are wrinkles, unevenness; color uniformity, whether the color is consistent, and whether there are color spots or stripes; width consistency, whether the width meets the standards and is stable; slitting quality, whether the edges are neat, and whether there are burrs, etc.

[0062] The finished product qualification index abnormal traceability module is used to trace the raw materials and production link data based on the finished product qualification index of this batch of spunlace non-woven fabrics. When the finished product rate is abnormal, it can locate the cause and propose improvement measures.

[0063] In a specific embodiment of the present invention, when the yield rate is abnormal, the raw materials and production process data are traced back to locate the cause and propose improvement measures, which specifically include:

[0064] When the qualified index of the finished product of spunlace non-woven fabric is abnormal, the system traceability mechanism is triggered to retrieve the whole chain data of the raw material batch, equipment parameters, environmental monitoring, etc. of the abnormal batch, verify the supplier information and warehousing inspection report, re-check the physical properties and functional indicators such as raw material fiber length and strength, and check batch defects; trace back the real-time data of workshop temperature, humidity and cleanliness, verify the equipment parameters such as spunlace head pressure, slitting knife wear and fault downtime rate, analyze the online monitoring data of the production process such as gram weight, width, defect area, locate the cause of the abnormal finished product rate, and take targeted measures according to the problem.

[0065] It should be noted that the present invention also includes a database for storing reference original data, including the raw material qualification rate threshold, the maximum threshold of the fiber physical property unqualified rate, the maximum threshold of the temperature fluctuation value, the maximum threshold of the humidity stability value, the maximum threshold of the cleanliness compliance rate, the maximum threshold of the water jet head pressure deviation value, the maximum threshold of the slitting knife wear index, the maximum threshold of the equipment failure downtime rate, and the maximum and minimum values ​​of the finished product appearance qualification value.

[0066] Reference Figure 2 As shown, the second aspect of the present invention provides a 5G-based thermal power plant safety monitoring system, including: S1. Spunlace non-woven fabric related data collection, used to collect relevant data of this batch of spunlace non-woven fabrics, the relevant data including raw material data, production workshop data and finished product data;

[0067] S2. Raw material qualification performance evaluation, used to evaluate the raw material qualification index of this batch of spunlace nonwoven fabrics based on the raw material data of the spunlace nonwoven fabrics;

[0068] S3. Production workshop performance evaluation, based on the raw material data of spunlace nonwovens, is used to evaluate the production performance qualification index of this batch of spunlace nonwovens, including the workshop environment compliance index, equipment operation performance index, and production process product qualification index, and to assess the impact of various aspects of the production workshop on the finished spunlace nonwovens;

[0069] S4 finished product performance evaluation is used to evaluate the finished product qualification index of spunlace nonwovens based on the finished product data of spunlace nonwovens;

[0070] S5 finished product qualification index abnormal traceability is used based on the finished product qualification index of this batch of spunlace non-woven fabrics. When the finished product rate is abnormal, it can trace the raw materials and production link data, locate the cause and propose improvement measures.

Claims

1. A spunlace nonwoven production workshop yield management system, characterized in that: include: The spunlace nonwoven fabric related data collection module is used to collect the relevant data of this batch of spunlace nonwoven fabrics, including raw material data, production workshop data and finished product data; The raw material qualification performance evaluation module is used to evaluate the raw material qualification index of this batch of spunlace nonwoven fabrics based on the raw material data of the spunlace nonwoven fabrics; The production workshop performance evaluation module is used to evaluate the production performance qualification index of this batch of spunlace nonwovens based on the raw material data of spunlace nonwovens, including the workshop environment compliance index, equipment operation performance index and production process product qualification index, and evaluate the impact of various aspects of the production workshop on the finished spunlace nonwovens; Finished product performance evaluation module, used to evaluate the finished product qualification index of spunlace nonwovens based on the finished product data of spunlace nonwovens; The finished product qualification index abnormal traceability module is used to trace the raw materials and production link data based on the finished product qualification index of this batch of spunlace non-woven fabrics. When the finished product rate is abnormal, it can locate the cause and propose improvement measures.

2. The spunlace nonwoven fabric production workshop yield management system according to claim 1, characterized in that: The data collected about the spunlace nonwoven fabric includes raw material data, production workshop data and finished product data, which specifically include: Raw material data includes the total number of samples inspected, the number of samples that meet all performance requirements in the inspection batch, the fiber length of each sample, the fiber strength of the sample, and the fiber fineness of the sample; Production workshop data includes workshop environment data, workshop equipment data, and online production process data. The workshop environment data includes the temperature, humidity, and air particle concentration of each monitoring point in the spunlace nonwoven production workshop at each time point. The workshop equipment data includes the duration of machine failure downtime, the real-time pressure of the spunlace head at each time point, the current total slitting length, and the machine failure downtime. The online production process data includes the weight of the product, the real-time width, the defect area, and the number of defects. Finished product data includes the appearance qualification value, temperature, absorbance at a specific wavelength, burning time, and damaged area of ​​each finished product sample; due to the different dimensions of the data in the calculation, the data needs to be normalized and the collected data needs to be quantified into values ​​between 0 and 1.

3. The yield management system for a spunlace nonwoven fabric production workshop according to claim 2, characterized in that: The raw material qualification index for evaluating the spunlace nonwoven fabric of this batch based on the raw material data of the spunlace nonwoven fabric specifically includes: A1. Extract the raw material data of spunlace nonwoven fabrics from the relevant data of spunlace nonwoven fabrics and evaluate the qualified rate of the raw materials of this batch of spunlace nonwoven fabrics. i is any integer greater than 2, which is the sample number for random inspection, where N i is the number of samples that meet all performance requirements in the random inspection batch; when R≥R′, the raw material quality is stable; when R<R′, R′ is the raw material qualification rate threshold of the spunlace nonwoven production workshop; A2. Evaluate the qualified index of the physical properties of this batch of spunlace non-woven fabric raw materials i is any integer greater than 2, and is the sample number for random inspection. Q i Indicates whether the physical properties of the raw fiber of spunlace nonwoven fabric are qualified. Q i =0 means the fiber physical properties are qualified, Q i =1 means the fiber physical properties are unqualified, is the fiber length deviation of the ith sample of spunlace nonwoven fabric, is the fiber fineness deviation of the i-th sample, is the fiber strength deviation of the i-th sample.

4. The yield management system for a spunlace nonwoven fabric production workshop according to claim 2, characterized in that: The evaluation of the workshop environment compliance index specifically includes: evaluating the workshop environment compliance index of this batch of spunlace nonwoven fabrics based on the workshop environment data of the spunlace nonwoven fabrics, B1. Record the temperature of each monitoring point at each time point. The difference between the highest and lowest temperatures at the same monitoring point within a fixed period is the temperature fluctuation value of the monitoring point, and the temperature stability index is obtained. j is any integer greater than 2, which is the number of the monitoring point, where T j is the temperature fluctuation value of the jth monitoring point; B2. Record the temperature difference of each monitoring point to obtain the humidity stability index m is any integer greater than 2, and the temperature and humidity sensor is used to collect data, where H m is the humidity value at the mth moment, is the average humidity; B3. Based on the workshop environment data of spunlace nonwoven fabrics, and after data processing, the cumulative time that the air particle concentration in the production workshop of this batch of spunlace nonwoven fabrics continuously meets the cleanliness standard is obtained, and the cleanliness compliance rate in the production workshop is obtained. where t d is the cumulative time during the production period when the air particle concentration continues to meet the cleanliness standard, and t′ is the actual operating time from the start to the shutdown of the production line.

5. The yield management system for a spunlace nonwoven fabric production workshop according to claim 2, characterized in that: The specific steps of evaluating the equipment operation performance index are: evaluating and obtaining the production process product qualification index of this batch of spunlace nonwoven fabrics based on the workshop equipment data of the spunlace nonwoven fabrics; C1. Pressure management of water jet nozzles in workshop equipment, pressure deviation value P of water jet nozzles w = | P ws -P′ | , where P ws is the real-time pressure of the water jet of the w-th device, and P′ is the set pressure of the water jet; C2. Management of wear life of slitting knife in workshop equipment, wear index of slitting knife Where W wt is the current total cutting length of the w-th device, and W′ is the upper limit of the blade cutting life; C3. Workshop equipment failure management, equipment failure downtime rate Among them B 停 is the machine downtime, and B′ is the planned production time.

6. The yield management system for a spunlace nonwoven production workshop according to claim 2, characterized in that: The specific steps of evaluating the qualified index of the products in the production process include: evaluating and obtaining the qualified index of the products in the production process of the current batch of spunlace nonwoven fabrics based on the online data of the production process of the spunlace nonwoven fabrics, D1. Online qualified rate of weight Among them G f is the number of each area of ​​the product with a grammage within the standard range, and b is the total number of monitored areas of the product; D2. Width deviation ΔE k =|E k -E′|, where E i is the real-time width of the product produced by the kth roll, and E′ is the standard width; D3. Defect area where X k is the kth defect area of ​​the product, and h is the total number of defects detected on the product.

7. The yield management system for a spunlace nonwoven production workshop according to claim 6, characterized in that: The specific steps for evaluating the impact of various aspects of the production workshop on the finished spunlace nonwoven fabric are as follows: Workshop environment compliance index When N=0, it means that the workshop environment conformity index meets the standard; when N=1, it means that the workshop environment conformity index does not meet the standard. is the maximum threshold of temperature fluctuation value, is the maximum threshold of humidity stability, D max is the maximum threshold value of cleanliness compliance rate; Equipment operation performance index When M=0, it means that the equipment operation performance index meets the standard; when M=1, it means that the equipment operation performance index does not meet the standard. max is the maximum threshold of the water jet head pressure deviation value, W max is the maximum threshold of the slitting knife wear index, B max The maximum threshold for equipment failure downtime rate.

8. The yield management system for a spunlace nonwoven fabric production workshop according to claim 7, characterized in that: The evaluation of the qualified index of the finished product of the spunlace non-woven fabric is specifically to sample each batch of products, take 1 meter samples at the beginning, middle and end of each roll, avoid end face errors, and conduct inspection and determine whether it is qualified, which specifically includes: Finished product appearance qualified value r is any integer greater than 2, which is the number of the sample taken, where X is the qualified value of the finished product appearance, and M' is the standard area of ​​a single roll; Vertical burning test value Where T 自 Extinction is the time it takes for the sample to extinguish itself after burning, T 标 is the standard time for self-extinguishing, C 损毁 is the damaged length of the sample after combustion, C 标 It is the standard damaged length after burning. When Y=1, the finished non-woven fabric of this batch is qualified; when Y=0, the finished non-woven fabric of this batch is unqualified. Moisture content of spunlace nonwoven finished products in T a The cloth is the actual cloth surface temperature of the ath sample, T is the standard calibration temperature, and A a1450 is the absorbance of water molecules in the ath sample at a wavelength of 1450nm infrared light, A a1300 is the reference absorbance of water molecules in the ath sample at a wavelength of 1300nm infrared light, is the fiber background absorption, in order to eliminate the material difference, ε, β, γ are weight coefficients, when K a ≥K max When K min <K a <K max When K a ≤K min When the moisture content of the finished product reaches the standard; (X max ,X min ) Specifically, the maximum and minimum values ​​of the qualified appearance of the finished product; According to the finished product appearance qualified value, vertical burning test value and finished product moisture content of the spunlace non-woven fabric finished product samples, the finished product qualified index A=X×g1+Y×g2+K×g3 is obtained, where g1, g2, and g3 are the weight coefficients of the finished product appearance qualified value, vertical burning test value, and finished product moisture content, respectively, and g1+g2+g3=1.

9. The yield management system for a spunlace nonwoven fabric production workshop according to claim 8, characterized in that: When the yield rate is abnormal, trace the raw materials and production process data, locate the cause and propose improvement measures, which specifically include: When the qualified index of the finished product of spunlace non-woven fabric is abnormal, the system traceability mechanism is triggered to retrieve the whole chain data of the raw material batch, equipment parameters, environmental monitoring, etc. of the abnormal batch, verify the supplier information and warehousing inspection report, re-check the physical properties and functional indicators such as raw material fiber length and strength, and check batch defects; trace back the real-time data of workshop temperature, humidity and cleanliness, verify the equipment parameters such as spunlace head pressure, slitting knife wear and fault downtime rate, analyze the online monitoring data of the production process such as gram weight, width, defect area, locate the cause of the abnormal finished product rate, and take targeted measures according to the problem.

10. A method for implementing the spunlace nonwoven fabric production workshop yield management system according to any one of claims 1 to 9, comprising: S1. Spunlace nonwoven fabric related data collection, used to collect relevant data of this batch of spunlace nonwoven fabrics, the relevant data including raw material data, production workshop data and finished product data; S2. Raw material qualification performance evaluation, used to evaluate the raw material qualification index of this batch of spunlace nonwoven fabrics based on the raw material data of the spunlace nonwoven fabrics; S3. Production workshop performance evaluation, based on the raw material data of spunlace nonwovens, is used to evaluate the production performance qualification index of this batch of spunlace nonwovens, including the workshop environment compliance index, equipment operation performance index, and production process product qualification index, and to assess the impact of various aspects of the production workshop on the finished spunlace nonwovens; S4 finished product performance evaluation is used to evaluate the finished product qualification index of spunlace nonwovens based on the finished product data of spunlace nonwovens; S5 finished product qualification index abnormal traceability is used based on the finished product qualification index of this batch of spunlace non-woven fabrics. When the finished product rate is abnormal, it can trace the raw materials and production link data, locate the cause and propose improvement measures.

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